Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Potential biomarkers of acute myocardial infarction based on weighted gene co-expression network analysis

25 Jan 2019

Abstract excerpt

BACKGROUND: Acute myocardial infarction (AMI) is the common cause of mortality in developed countries. The feasibility of whole-genome gene expression analysis to identify outcome-related genes and dysregulated pathways remains unknown. Molecular marker such as BNP, CRP and other serum inflammatory markers have got the notice at this point. However, these biomarkers exhibit elevated levels in patients with...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Adipokines, Inflammation, and Metabolic Diseases
Share to Cardiac Fibrosis and Remodeling
Share to GDF15 and Related Biomarkers

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 30683112
DOI: 10.1186/s12938-019-0625-6

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Potential biomarkers of acute myocardial infarction based on weighted gene co-expression network analysisPMID 30683112Read ↗

Identification of Potential Biomarkers Associated with Acute Myocardial Infarction by Weighted Gene Coexpression Network AnalysisSemantic proximity Read ↗

Biomarkers identification for acute myocardial infarction detection via weighted gene co-expression network analysisSemantic proximity Read ↗

Weighted Gene Co-Expression Network Analysis Identifies Critical Genes in the Development of Heart Failure After Acute Myocardial InfarctionSemantic proximity Read ↗

Identification of Candidate Genes and MicroRNAs for Acute Myocardial Infarction by Weighted Gene Coexpression Network AnalysisSemantic proximity Read ↗

Identification of Key Genes as Early Warning Signals of Acute Myocardial Infarction Based on Weighted Gene Correlation Network Analysis and Dynamic Network Biomarker AlgorithmSemantic proximity Read ↗

Potential Biomarkers of Acute Myocardial Infarction Based on Co-Expression Network AnalysisSemantic proximity Read ↗

Weighted gene co-expression network analysis identifies specific modules and hub genes related to coronary artery disease.Semantic proximity Read ↗

Gene regulatory network analysis identifies key genes and regulatory mechanisms involved in acute myocardial infarction using bulk and single cell RNA-seq dataSemantic proximity Read ↗

Identification of key genes associated with acute myocardial infarction using WGCNA and two-sample mendelian randomization studySemantic proximity Read ↗

Identification of Immune-Related Genes in Patients with Acute Myocardial Infarction Using Machine Learning MethodsSemantic proximity Read ↗

FCER1G and PTGS2 Serve as Potential Diagnostic Biomarkers of Acute Myocardial Infarction Based on Integrated Bioinformatics AnalysesSemantic proximity Read ↗

Identification of Co-Expressed Central Genes and Transcription Factors in Acute Myocardial Infarction and Diabetic NephropathySemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.